Copy Create Video Forgery Detection Techniques Using Frame Correlation Difference by Referring SVM Classifier
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Abstract
Video Forensic is a new research avenue in computer forensics. Usually, passive forgery detection techniques have much more import then active forgery techniques to resolve the cost and efficiency of computational video. Forgery detection methods available in copy-move and copy-paste type of forgery. here we propose an algorithm for copy create, which is a combination of copy-move and copy-paste region of video forgery by using frame correlation differences between sets of I-frame in the forged video by using SVM Classifier. We are successful in authenticating the tested video is original or forgery at the same time it returns good result identifying the different I-frame sequence in given forgery videos. Forgery video inputs are customized by referring standard available data set like SULPA, REWIND, VTD, and CVIP
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